fast methods for sparse ± UniformScaling

[stevengj]

As described in this discourse thread, if A is a sparse matrix then A + x*I is hitting a specialized method, whereas A' + x*I hits a generic method that mutates one element of the diagonal at a time, which is very slow for sparse matrices.

Should be easily fixable by adding some specialized methods, e.g.

import Base: +, -
using LinearAlgebra: AdjOrTrans, wrapperop
(+)(A::AdjOrTrans{<:Any, <:AbstractSparseMatrix}, J::UniformScaling{<:Number}) =
    wrapperop(A)(parent(A) + wrapperop(A)(J))
(-)(A::AdjOrTrans{<:Any, <:AbstractSparseMatrix}, J::UniformScaling{<:Number}) =
    wrapperop(A)(parent(A) - wrapperop(A)(J))
(+)(J::UniformScaling{<:Number}, A::AdjOrTrans{<:Any, <:AbstractSparseMatrix}) =
    wrapperop(A)(wrapperop(A)(J) + parent(A))
(-)(J::UniformScaling{<:Number}, A::AdjOrTrans{<:Any, <:AbstractSparseMatrix}) =
    wrapperop(A)(wrapperop(A)(J) - parent(A))

Should be an easy PR for someone?

Should be fixed by JuliaLang/LinearAlgebra.jl#1366